Abstract
Future urban energy systems planning, incorporates various interconnected components including smart grids, electric vehicles, renewable energy sources, heating, and cooling systems. This chapter is the brief introduction to the data-driven energy system with special focus on methods and algorithms for hedging against the ever-increasing uncertainty that surrounds their operation. Special attention is paid to operation control, stochastic optimization, and introduction of the digital twins to achieve higher resilience in future energy systems of smart cities.
| Original language | English |
|---|---|
| Title of host publication | Solving Urban Infrastructure Problems Using Smart City Technologies |
| Subtitle of host publication | Handbook on Planning, Design, Development, and Regulation |
| Publisher | Elsevier |
| Pages | 571-597 |
| Number of pages | 27 |
| ISBN (Electronic) | 9780128168165 |
| ISBN (Print) | 9780128168172 |
| DOIs | |
| State | Published - 1 Jan 2020 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Keywords
- Energy management, smart grids, resilient future energy systems, vehicle-to-grid, microgrids, model predictive control, optimization
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